Warning: This dashboard contains the results of a predictive model that was not built by an epidemiologist.

Based on data up to: 2020-06-23

World map (interactive)

Includes only countries with at least 1000 reported cases or at least 20 reported deaths.

Tip: Select columns to show on map to from the dropdown menus. The map is zoomable and draggable.

Tables

Projected need for ICU beds

Countries sorted by current ICU demand, split into Growing and Recovering countries by current transmission rate.

  • Details of estimation and prediction calculations are in Appendix, as well as Plots of model predictions.
  • Column definitions:- Estimated ICU need per 100k population: number of ICU beds estimated to be needed per 100k population by COVID-19 patents. - Estimated daily infection rate: daily percentage rate of new infections relative to active infections during last 5 days.
    • Projected ICU need per 100k in 14 days: self explanatory.
    • Projected ICU need per 100k in 30 days: self explanatory.
    • ICU capacity per 100k: number of ICU beds per 100k population.
    • Estimated ICU Spare capacity per 100k: estimated ICU capacity per 100k population based on assumed normal occupancy rate of 70% and number of ICU beds (only for countries with ICU beds data).

Tip: The red (need for ICU) and the blue (ICU spare capacity) bars are on the same 0-10 scale, for easy visual comparison of columns.

Growing countries (transmission rate above 5%)

Estimated
current
ICU need
per 100k
population		 Estimated
daily
transmission
rate		 Projected
ICU need
per 100k
In 14 days		 Projected
ICU need
per 100k
In 30 days		 Pre-COVID
ICU
capacity
per 100k		 Pre-COVID
Estimated ICU
Spare capacity
per 100k
Country/Region
Sweden 9.50 5.2% ± 1.5% noisy data noisy data 5.8 1.7
Bahrain 7.10 5.6% ± 0.4% 7.5 ± 1.0 8.1 ± 2.3 - -
Panama 6.74 7.1% ± 0.7% 8.6 ± 1.8 11.3 ± 5.0 - -
Brazil 6.74 6.8% ± 1.4% 8.1 ± 3.1 noisy data - -
US 6.41 6.2% ± 0.1% 7.2 ± 0.5 8.4 ± 1.3 34.7 10.4
Moldova 4.45 5.9% ± 0.8% 4.9 ± 1.4 noisy data - -
North Macedonia 4.19 5.5% ± 0.8% 4.4 ± 1.0 noisy data - -
Oman 3.87 6.9% ± 0.9% 4.9 ± 1.1 6.5 ± 3.0 14.6 4.4
Saudi Arabia 2.83 5.4% ± 0.4% 2.9 ± 0.3 3.1 ± 0.7 22.8 6.8
Bolivia 2.57 7.5% ± 0.5% 3.5 ± 0.4 4.9 ± 1.2 - -
Colombia 1.99 9.4% ± 1.9% noisy data noisy data - -
Dominican Republic 1.94 7.1% ± 0.6% 2.5 ± 0.6 3.4 ± 1.7 - -
South Africa 1.75 7.9% ± 0.5% 2.5 ± 0.3 3.8 ± 0.8 - -
Argentina 1.75 8.1% ± 0.6% 2.6 ± 0.4 4.2 ± 1.3 - -
Mexico 1.48 6.5% ± 0.3% 1.7 ± 0.1 2.0 ± 0.4 1.2 0.4
Azerbaijan 1.45 7.4% ± 0.1% 2.0 ± 0.1 2.9 ± 0.2 - -
Israel 1.38 7.8% ± 0.4% 2.0 ± 0.7 noisy data - -
Bosnia 1.36 9.0% ± 2.9% noisy data noisy data - -
Ukraine 1.29 6.2% ± 0.3% 1.5 ± 0.2 1.8 ± 0.4 - -
Honduras 1.25 9.2% ± 2.0% noisy data noisy data - -
Romania 1.21 5.6% ± 0.2% 1.3 ± 0.2 1.4 ± 0.4 - -
Gabon 1.10 5.2% ± 2.6% noisy data noisy data - -
Albania 1.08 6.5% ± 0.7% 1.3 ± 0.3 1.7 ± 0.8 - -
Bulgaria 1.03 6.4% ± 0.9% 1.2 ± 0.4 noisy data - -
Kazakhstan 0.91 8.2% ± 1.1% 1.4 ± 0.6 noisy data 21.3 6.4
Luxembourg 0.85 5.9% ± 0.1% 0.9 ± 0.5 noisy data 24.8 7.4
El Salvador 0.84 7.2% ± 0.3% 1.1 ± 0.1 1.6 ± 0.3 - -
Serbia 0.83 5.6% ± 0.0% 0.9 ± 0.0 1.0 ± 0.1 - -
Guatemala 0.68 7.2% ± 1.4% 0.9 ± 0.3 noisy data - -
Iraq 0.66 8.8% ± 0.5% 1.0 ± 0.1 1.8 ± 0.3 - -
Bangladesh 0.63 5.8% ± 0.1% 0.7 ± 0.0 0.8 ± 0.0 0.7 0.2
Costa Rica 0.61 8.4% ± 1.1% 1.0 ± 0.3 noisy data - -
Pakistan 0.58 5.2% ± 0.7% 0.6 ± 0.1 0.6 ± 0.2 1.5 0.4
Czechia 0.57 5.6% ± 0.4% 0.6 ± 0.3 noisy data 11.6 3.5
Mauritania 0.55 8.6% ± 1.2% 0.8 ± 0.2 noisy data - -
Kyrgyzstan 0.47 13.9% ± 4.6% noisy data noisy data - -
Egypt 0.42 5.7% ± 0.4% 0.5 ± 0.0 0.5 ± 0.1 - -
Nepal 0.41 7.2% ± 0.7% 0.5 ± 0.1 0.8 ± 0.2 2.8 0.8
Central African Republic 0.32 5.7% ± 1.8% 0.3 ± 0.2 noisy data - -
India 0.31 7.1% ± 0.1% 0.4 ± 0.0 0.6 ± 0.0 5.2 1.6
Nicaragua 0.31 noisy data noisy data noisy data - -
Iceland 0.28 6.2% ± 0.1% noisy data noisy data 9.1 2.7
Ghana 0.20 5.8% ± 1.3% 0.2 ± 0.1 noisy data - -
Croatia 0.19 13.6% ± 0.3% noisy data noisy data - -
Cameroon 0.19 9.5% ± 3.3% noisy data noisy data - -
Philippines 0.18 7.0% ± 0.7% 0.2 ± 0.1 noisy data 2.2 0.7
West Bank and Gaza 0.17 24.0% ± 4.7% noisy data noisy data - -
Venezuela 0.17 7.0% ± 0.9% 0.2 ± 0.0 0.3 ± 0.1 - -
Cote d'Ivoire 0.16 7.2% ± 1.7% 0.2 ± 0.1 noisy data - -
Slovenia 0.15 7.2% ± 0.3% noisy data noisy data 6.4 1.9
Morocco 0.15 10.5% ± 1.6% noisy data noisy data - -
Indonesia 0.13 5.5% ± 0.3% 0.1 ± 0.0 0.2 ± 0.0 2.7 0.8
Uzbekistan 0.12 7.0% ± 0.4% 0.2 ± 0.0 0.2 ± 0.1 - -
Senegal 0.12 5.3% ± 0.7% 0.1 ± 0.0 noisy data - -
Lebanon 0.12 6.8% ± 0.9% noisy data noisy data - -
Algeria 0.12 5.0% ± 0.1% 0.1 ± 0.0 0.1 ± 0.0 - -
Uruguay 0.09 8.9% ± 0.6% noisy data noisy data - -
Congo (Brazzaville) 0.09 noisy data noisy data noisy data - -
Liberia 0.07 7.5% ± 2.2% noisy data noisy data - -
Slovakia 0.06 6.3% ± 0.4% noisy data noisy data 9.2 2.8
Australia 0.05 6.4% ± 0.2% noisy data noisy data 9.1 2.7
Nigeria 0.04 6.1% ± 0.6% 0.0 ± 0.0 0.1 ± 0.0 - -
Kenya 0.04 5.7% ± 1.5% 0.0 ± 0.0 noisy data - -
Madagascar 0.03 8.5% ± 1.3% 0.0 ± 0.0 noisy data - -
Ethiopia 0.03 6.5% ± 2.9% noisy data noisy data - -
Congo (Kinshasa) 0.03 5.9% ± 0.9% 0.0 ± 0.0 noisy data - -
Tunisia 0.02 5.8% ± 0.5% noisy data noisy data - -
New Zealand 0.02 8.1% ± 0.0% 0.0 ± 0.0 noisy data - -
Niger 0.00 5.5% ± 0.5% noisy data noisy data - -
China 0.00 6.1% ± 0.0% noisy data noisy data 3.6 1.1

Recovering countries (tranmission rate below 5%)

Estimated
current
ICU need
per 100k
population		 Estimated
daily
transmission
rate		 Projected
ICU need
per 100k
In 14 days		 Projected
ICU need
per 100k
In 30 days		 Pre-COVID
ICU
capacity
per 100k		 Pre-COVID
Estimated ICU
Spare capacity
per 100k
Country/Region
Chile 21.83 4.1% ± 0.4% 18.9 ± 2.1 15.8 ± 3.6 - -
Qatar 10.72 3.6% ± 0.1% 8.8 ± 0.4 6.8 ± 0.6 - -
Armenia 10.10 4.9% ± 0.5% 9.8 ± 1.4 9.5 ± 2.9 - -
Belarus 6.55 3.5% ± 0.1% 5.4 ± 0.4 4.2 ± 0.6 - -
Peru 6.40 3.8% ± 0.2% 5.3 ± 0.4 4.3 ± 0.6 - -
Kuwait 4.69 4.6% ± 0.2% 4.4 ± 0.4 4.0 ± 0.8 - -
Russia 4.63 4.3% ± 0.1% 4.2 ± 0.1 3.8 ± 0.2 8.3 2.5
Singapore 4.28 2.5% ± 0.1% 3.1 ± 0.3 2.0 ± 0.4 11.4 3.4
Portugal 3.62 5.0% ± 0.1% 3.6 ± 0.4 3.5 ± 0.8 4.2 1.3
United Kingdom 2.35 3.3% ± 0.1% 1.8 ± 0.1 1.4 ± 0.2 6.6 2.0
Djibouti 1.58 1.1% ± 0.2% 0.9 ± 0.1 0.5 ± 0.1 - -
Canada 1.45 2.9% ± 0.1% 1.1 ± 0.1 0.8 ± 0.1 13.5 4.0
Maldives 1.35 3.6% ± 0.4% 1.1 ± 0.3 0.9 ± 0.4 - -
Ecuador 1.34 4.8% ± 0.9% noisy data noisy data - -
Belgium 1.31 2.9% ± 0.2% 1.0 ± 0.4 noisy data 15.9 4.8
Iran 1.16 4.9% ± 0.1% 1.1 ± 0.0 1.1 ± 0.1 4.6 1.4
UAE 1.07 3.6% ± 0.0% 0.9 ± 0.0 0.7 ± 0.0 - -
Spain 1.04 3.1% ± 0.0% 0.8 ± 0.1 0.6 ± 0.1 9.7 2.9
Netherlands 0.94 2.3% ± 0.0% 0.7 ± 0.0 0.4 ± 0.1 6.4 1.9
Poland 0.91 3.8% ± 0.0% 0.8 ± 0.0 0.6 ± 0.0 6.9 2.1
France 0.83 4.6% ± 0.1% 0.8 ± 0.2 noisy data 11.6 3.5
Denmark 0.83 4.2% ± 0.4% noisy data noisy data 6.7 2.0
Italy 0.77 1.6% ± 0.1% 0.5 ± 0.1 noisy data 12.5 3.8
Turkey 0.77 4.5% ± 0.0% 0.7 ± 0.0 0.7 ± 0.0 47.1 14.1
Germany 0.69 4.9% ± 0.1% 0.7 ± 0.1 0.7 ± 0.2 29.2 8.8
Ireland 0.63 0.8% ± 0.0% 0.4 ± 0.0 0.2 ± 0.0 6.5 1.9
Austria 0.41 4.8% ± 0.1% 0.4 ± 0.1 noisy data 21.8 6.5
Finland 0.40 1.6% ± 0.1% 0.3 ± 0.0 0.1 ± 0.1 6.1 1.8
Estonia 0.37 0.9% ± 0.0% 0.2 ± 0.0 0.1 ± 0.0 14.6 4.4
Switzerland 0.36 4.0% ± 0.0% 0.3 ± 0.1 noisy data 11.0 3.3
Haiti 0.35 3.1% ± 0.9% 0.3 ± 0.1 noisy data - -
Equatorial Guinea 0.30 0.0% ± 0.0% 0.2 ± 0.0 0.1 ± 0.0 - -
Norway 0.27 3.5% ± 0.1% 0.2 ± 0.1 noisy data 8.0 2.4
Afghanistan 0.27 3.2% ± 0.3% 0.2 ± 0.0 0.2 ± 0.0 - -
Lithuania 0.26 2.7% ± 0.1% 0.2 ± 0.0 0.1 ± 0.1 15.5 4.6
Tajikistan 0.20 3.3% ± 0.1% 0.2 ± 0.0 0.1 ± 0.0 - -
Greece 0.18 4.2% ± 0.1% 0.2 ± 0.0 0.1 ± 0.1 6.0 1.8
Latvia 0.15 1.0% ± 0.1% 0.1 ± 0.0 0.0 ± 0.0 9.7 2.9
Guinea-Bissau 0.14 4.1% ± 1.3% noisy data noisy data - -
Hungary 0.14 1.8% ± 0.1% 0.1 ± 0.0 0.1 ± 0.0 13.8 4.1
Paraguay 0.10 4.8% ± 0.6% 0.1 ± 0.0 noisy data - -
Sudan 0.09 4.9% ± 1.3% 0.1 ± 0.0 noisy data - -
Cuba 0.09 1.7% ± 0.1% 0.1 ± 0.0 0.0 ± 0.0 - -
Guinea 0.09 3.1% ± 0.5% 0.1 ± 0.0 noisy data - -
South Korea 0.07 5.0% ± 0.1% 0.1 ± 0.0 noisy data 10.6 3.2
South Sudan 0.07 2.5% ± 0.5% 0.1 ± 0.0 0.0 ± 0.0 - -
Japan 0.07 4.5% ± 0.1% 0.1 ± 0.0 0.1 ± 0.0 7.3 2.2
Sierra Leone 0.06 3.2% ± 0.5% 0.0 ± 0.0 0.0 ± 0.0 - -
Sri Lanka 0.05 2.2% ± 0.8% 0.0 ± 0.0 noisy data 2.3 0.7
Malaysia 0.04 1.6% ± 0.1% 0.0 ± 0.0 0.0 ± 0.0 3.4 1.0
Somalia 0.04 2.5% ± 0.6% 0.0 ± 0.0 noisy data - -
Jordan 0.03 3.5% ± 0.5% 0.0 ± 0.0 noisy data - -
Mali 0.02 2.4% ± 0.5% 0.0 ± 0.0 0.0 ± 0.0 - -
Zambia 0.02 2.9% ± 1.3% noisy data noisy data - -
Yemen 0.02 3.1% ± 0.9% 0.0 ± 0.0 0.0 ± 0.0 - -
Chad 0.01 0.9% ± 0.2% 0.0 ± 0.0 0.0 ± 0.0 - -
Thailand 0.00 3.4% ± 0.1% 0.0 ± 0.0 noisy data 10.4 3.1
Burkina Faso 0.00 2.7% ± 0.2% 0.0 ± 0.0 noisy data - -
Tanzania 0.00 0.0% ± 0.0% 0.0 ± 0.0 0.0 ± 0.0 - -

Appendix

Interactive plot of model predictions and past data

Tip: Choose a country from the drop-down menu to see the calculations used in the tables above and the dynamics of the model.

Projected Affected Population percentages

Top 20 countries with most estimated recent cases.

  • Sorted by number of estimated recent cases during the last 5 days.
  • Column definitions:- Estimated recent cases in last 5 days: self explanatory. - Estimated total affected population percentage: estimated percentage of total population already affected (infected, recovered, or dead).
    • Estimated daily tranmission rate: daily percentage rate of recent infections relative to active infections during last 5 days.
    • Projected total affected percentage in 14 days: of population.
    • Projected total affected percentage in 30 days: of population.
    • Lagged fatality rate: reported total deaths divided by total cases 8 days ago.
Estimated
new cases
in last 5 days		 Estimated
total
affected
population
percentage		 Estimated
daily
tranmission
rate		 Projected
total
affected
percentage
In 14 days		 Projected
total
affected
percentage
In 30 days		 Lagged
fatality
percentage
Country/Region
Brazil 1,568,956 5.2% 6.8% ± 1.4% 7.5% ± 1.5% 10.8% ± 5.0% 5.9%
US 909,052 4.2% 6.2% ± 0.1% 5.0% ± 0.1% 6.1% ± 0.3% 5.7%
Mexico 765,277 4.5% 6.5% ± 0.3% 6.3% ± 0.3% 8.9% ± 0.8% 15.6%
India 704,305 0.3% 7.1% ± 0.1% 0.5% ± 0.0% 0.8% ± 0.0% 4.2%
Iraq 191,344 2.0% 8.8% ± 0.5% 3.9% ± 0.3% 7.6% ± 1.1% 5.9%
Pakistan 184,501 0.7% 5.2% ± 0.7% 0.9% ± 0.1% 1.2% ± 0.2% 2.5%
South Africa 160,974 1.4% 7.9% ± 0.5% 2.3% ± 0.2% 4.1% ± 0.6% 2.9%
Iran 136,486 2.8% 4.9% ± 0.1% 3.2% ± 0.0% 3.7% ± 0.1% 5.2%
Colombia 131,230 1.2% 9.4% ± 1.9% 2.3% ± 0.7% noisy data 4.7%
Egypt 106,143 0.8% 5.7% ± 0.4% 1.1% ± 0.1% 1.5% ± 0.2% 5.1%
Peru 101,958 5.0% 3.8% ± 0.2% 5.7% ± 0.1% 6.5% ± 0.3% 3.6%
Chile 83,032 4.3% 4.1% ± 0.4% 5.4% ± 0.3% 6.6% ± 0.7% 2.5%
United Kingdom 73,933 5.9% 3.3% ± 0.1% 6.1% ± 0.1% 6.3% ± 0.1% 14.4%
Indonesia 71,955 0.3% 5.5% ± 0.3% 0.3% ± 0.0% 0.4% ± 0.0% 6.5%
Bangladesh 69,889 0.3% 5.8% ± 0.1% 0.4% ± 0.0% 0.6% ± 0.0% 1.7%
Russia 64,626 0.7% 4.3% ± 0.1% 0.8% ± 0.0% 0.9% ± 0.0% 1.6%
Saudi Arabia 54,091 1.4% 5.4% ± 0.4% 1.9% ± 0.1% 2.4% ± 0.3% 1.0%
Philippines 45,740 0.3% 7.0% ± 0.7% 0.5% ± 0.1% 0.7% ± 0.2% 4.5%
Argentina 45,008 0.5% 8.1% ± 0.6% 0.9% ± 0.1% 1.6% ± 0.3% 3.3%
Ecuador 44,602 5.2% 4.8% ± 0.9% 5.8% ± 0.8% 6.6% ± 2.3% 9.0%

Methodology

  • I'm not an epidemiologist. This is an attempt to understand what's happening, and what the future looks like if current trends remain unchanged.
  • Everything is approximated and depends heavily on underlying assumptions.
  • Projection is done using a simple SIR model with (see examples) combined with the approach in Total Outstanding Cases:
    • Growth rate calculated over the 5 past days. This is pessimistic - because it includes the testing rate growth rate as well, and is slow to react to both improvements in test coverage and "flattening" due to social isolation.
    • Confidence bounds are calculated by from the weighted STD of the growth rate over the last 5 days. Model predictions are calculated for growth rates within 1 STD of the weighted mean. The maximum and minimum values for each day are used as confidence bands.
    • For projections (into future) very noisy projections (with broad confidence bounds) are not shown in the tables.
    • Recovery probability being 1/20 (for 20 days to recover) where the rate estimated from Total Outstanding Cases is too high (on down-slopes).
  • Total cases are estimated from deaths in each country:
    • Each country has different testing policy and capacity and cases are under-reported in some countries. Using an estimated IFR (fatality rate) we can estimate the number of cases some time ago by using the total deaths until today. We can than use this estimation to estimate the testing bias and multiply the current numbers by that.
    • IFRs for each country is estimated using the age IFRs from May 1 New York paper and UN demographic data for 2020. These IFRs can be found in df['age_adjusted_ifr'] column. Some examples: US - 0.98%, UK - 1.1%, Qatar - 0.25%, Italy - 1.4%, Japan - 1.6%.
    • The average fatality lag is assumed to be 8 days on average for a case to go from being confirmed positive (after incubation + testing lag) to death. This is the same figure used by "Estimating The Infected Population From Deaths".
    • Testing bias: the actual lagged fatality rate is than divided by the IFR to estimate the testing bias in a country. The estimated testing bias then multiplies the reported case numbers to estimate the true case numbers (=case numbers if testing coverage was as comprehensive as in the heavily tested countries).
  • ICU need is calculated and age-adjusted as follows:
    • UK ICU ratio was reported as 4.4% of active reported cases.
    • Using UKs ICU ratio and IFRs corrected for age demographics we can estimate each country's ICU ratio (the number of cases requiring ICU hospitalisation). For example using the IFR ratio between UK and Qatar to devide UK's 4.4% we get an ICU ratio of around 1% for Qatar which is also the ratio they report to WHO here.
    • Active cases are taken from the SIR model. The ICU need is calculated from reported cases rather than from total estimated active cases. This is because the ICU ratio (4.4%) is based on reported cases.
    • Pre COVID-19 ICU capacities are from Wikipedia (OECD countries mostly) and CCB capacities in Asia.
    • Pre COVID-19 ICU spare capacity is based on 70% normal occupancy rate (66% in US, 75% OECD)